The benefits and drawbacks of using dynamic scoring in the federal budget

Posted on February 12, 2015April 18, 2018 by Ed Paisley

One of the first actions taken by the U.S. House of Representatives this year was the approval of a rule change requiring so called dynamic scoring for some proposed legislation. Under the new rule, when the non-partisan U.S. Congressional Budget Office and Joint Committee on Taxation calculate the official budgetary cost of a special category of proposed legislation they will now have to include an estimate of the effects of the legislation on economic growth and the feedback effects of that growth on the budget. The new rule goes into effect this year.

This issue brief explains what dynamic scoring is, what legislation it must be applied to under the new House rule, and what its advantages and disadvantages are in general and then more specifically under the new rule. As explained in detail below, dynamic scoring has theoretical advantages but practical problems that undercut its usefulness. The use of dynamic scoring is likely to lead to greater budgetary uncertainty and, oftentimes, less accurate budget forecasts.

Most critically, from an economic perspective, the selective application of dynamic scoring to budgetary analysis as specified in the new House rule may bias careful evaluation of tax and spending proposals and lead to public policy distortions that will slow down long-run economic growth, weaken job creation, and undermine economic well–being. Understanding the problems with dynamic scoring and the macroeconomic models it relies on to predict future economic growth will be important in particular as Congress and the Obama Administration begin to build a new budget for the fiscal year beginning in October 2015.

Download the pdf version of this brief for a complete list of sources

What is dynamic scoring?

The U.S. Congressional Budget Office, a nonpartisan federal agency that provides economic and budget information to Congress, and the Joint Committee on Taxation, a nonpartisan committee of Congress that analyzes tax legislation, evaluate the budgetary consequences of proposed legislation. Under the law that will be superseded by the new House rule, CBO and JCT would “score” legislation by estimating how much revenue would be lost or gained by a tax change proposal and how much money would be spent or saved by spending proposals such as investments in roads or reductions in federal spending on space exploration.

Sometimes proposed legislation, such as the Patient Protection and Affordable Care Act, or Obamacare, involved both tax and spending changes. In those cases, the CBO and JCT calculated the net impact of both the spending and tax changes on the budget. In the case of Obamacare, for example, CBO and JCT calculated that the various tax and spending provisions of the proposed law would raise $486 billion in federal government revenue and increase federal spending by $356 billion over the ten-year period between 2010 and 2019. In giving their final score, they concluded that the “spending and revenue effects of enacting the Patient Protection and Affordable Care Act would yield a net reduction in federal deficits of $130 billion over the 2010-2019 period.”

It is important to note that when scoring, or calculating, the budgetary consequences of proposed legislation, CBO and JCT assumed that the legislation would have no effect on economic growth, although they did take into account many individual behavioral changes or microeconomic effects. The House of Representative’s proposed “dynamic” scoring method, therefore, is different from the old scoring method because, in estimating the fiscal consequence of some proposed legislation, it will require CBO and JCT to estimate the effects of that legislation on economic growth and then factor in the estimated growth effects on the budget.

In practical terms, this means that for the special class of legislation that will be subjected to dynamic scoring under the new House rule, the budgetary impact will be estimated to be less onerous than under the conventional scoring method when that legislation is deemed to increase economic growth. By the same logic, the dynamic score will be more onerous than the conventional score when that legislation is judged to reduce growth. But under the new House rule, what legislation must be dynamically scored?

Legislation subject to dynamic scoring under the new House rule

Under the new rule, CBO and JCT are required to incorporate an estimate of the growth or macroeconomic effects of “major legislation” into their official budget cost estimates. “Major legislation” is defined as tax bills or mandatory spending bills that cause an increase or decrease in revenues, outlays, or deficits of more than 0.25 percent of GDP (approximately $45 billion in 2015) in any given year. In addition, the chair of the House Budget Committee and, for revenue legislation only, the chair or vice chair of the Joint Committee on Taxation can designate other bills as “major legislation” even when they do not meet the 0.25 percent-of-GDP threshold.

At first glance, the new rule may seem evenhanded in its treatment of proposed tax and spending legislation. But it is not. Instead, it will apply almost exclusively to tax bills and rarely, if ever, to spending bills. The rule does not apply to spending bills that are “discretionary” as opposed to “mandatory” even if discretionary spending proposals exceed the 0.25 percent-of-GDP threshold. Thus, it does not apply to all the regular appropriations bills that include almost all spending or investment in infrastructure, education, health, research, science, national defense, and hundreds of other programs.

In addition, although dynamic scoring does apply to “mandatory” spending, the largest categories of which include Social Security and Medicare spending, it does so only if the budgetary effect of a change in annual spending in those programs due to proposed legislation exceeds 0.25 percent of GDP. It is unlikely that any proposed legislation will change annual spending in mandatory programs by $45 billion or more in any given year.

The upshot: Annual appropriations or investments of hundreds of billions of dollars in highway reconstruction, early childhood education, health care, and hundreds of other programs would not be subject to dynamic scoring, but a $45 billion tax proposal would be. For all practical purposes, therefore, the new rule will apply almost exclusively to tax legislation. Indeed, the House Committee on the Budget has noted that the rule would have applied to only 3 bills in the last Congress, all of which were primarily tax bills.

What’s more, as explained in the section below describing the problems with dynamic scoring, the selective nature of the new House rule undermines theoretical arguments in favor of dynamic scoring—arguments that might lead to the adoption and application of the method to budgetary analysis should the many obvious practical hurdles to accurate dynamic scoring be overcome some day. But before describing the problems of dynamic scoring, lets first look at its theoretical advantages.

Advantages of dynamic scoring in theory

Many government tax or spending policies are likely to influence economic growth. Economic research shows that during a recession some investments in infrastructure, education, and health care spur faster growth while cutbacks in these areas can slow growth. Likewise research shows that during an economic downturn some tax cuts stimulate growth while tax increases reduce growth. Measuring these effects is very difficult to do with extreme precision, but two ways would be to

Improve the accuracy of budget scoring
Remove the bias against pro-growth policies in budget scoring

Let’s look briefly at each of these theoretical advantages.

Improving accuracy of budget scores
When policy affects economic growth, it will have a feedback effect on the budget because the policy will affect the size of the economy and influence the level of public revenues and expenditures. A larger economy generates more tax revenue and reduces expenditures on many programs such as unemployment insurance. Similarly, a smaller economy produces less tax revenue and tends to increase spending on many programs such as nutrition assistance. Under perfect dynamic scoring, then, policies that promote growth will have a smaller budgetary cost and those that slow growth will have a larger budgetary cost than conventional CBO scoring predicts.

Ignoring these growth feedback effects causes conventional CBO scores to be less accurate than they otherwise could be. In an ideal world, every tax and spending proposal would be subjected to rigorous dynamic scoring so that we could get a true picture of the revenue and expenditure impacts of all legislation. The bottom line is that dynamic scoring, at least in theory, could provide policymakers and the public with more accurate budgetary information.

Remove bias against pro-growth policies
A second theoretical advantage of accurate dynamic scoring is that it is not biased against pro-growth policies compared to the current conventional scoring method. By ignoring macroeconomic effects, the conventional method overstates the true budgetary cost of pro-growth policies, such as infrastructure investments, and understates the cost of anti-growth policies.

Consider the conventional scoring of two policies with opposite impacts on economic growth. Policymakers weighing these two alternative proposals could be misled into rejecting the policy that has a positive impact on economic growth because it would be erroneously estimated to be more costly than it truly is, while they may be pushed into selecting the anti-growth policy because it would be falsely scored as less costly than it actually is.

Disadvantages of dynamic scoring in practice

The theoretical advantages of dynamic scoring, however, run into an array of serious practical hurdles. These practical considerations overwhelm the two theoretical reasons for considering dynamic scoring, namely:

Economists do not know how to accurately measure the growth effects of most policies
Dynamic scoring relies on less-than-accurate, theory-based macro models
The macro models undergirding dynamic scoring have numerous controversial and unproven built-in assumptions
The assumptions embedded in the macro models are not always carefully empirically based
Macro models exclude theoretically and empirically supported evidence of supply-side effects of public investment
Macro models exclude evidence-based effects of economic inequality
Macro models exclude evidence-based effects of numerous policies
Macro models provide different estimates of growth impacts of policy depending on guesses of how the policy may be financed

Let’s examine each of these disadvantages in turn.

Economists do not know how to accurately measure the growth effects of most policies
The first problem is that we do not know how to accurately measure the growth effects of most policies, a problem not faced by CBO and JCT under conventional scoring, which does not require estimates of the future growth effects of policy.

Future macroeconomic outcomes, such as growth, unemployment, and inflation are a function of a vast multitude of factors that include economic policies but also many other policy-unrelated events such as technological innovation, an outbreak of war, or a catastrophic weather phenomenon, to give just a few examples. Empirically identifying, isolating, and measuring the macroeconomic consequences of one specific policy is very time consuming, often involving many years of research, and is fraught with difficulty and large errors.

Dynamic scoring relies on less than accurate, theory based macro models
In practice, instead of basing budgetary estimates on empirically verified evidence, as is often done in conventional scoring, the CBO and JCT’s dynamic scoring relies on macroeconomic forecasting models that are theory based. There are a host of such macroeconomic models that attempt to measure growth effects and the subsequent feedback effects on the budget. They all come to different conclusions, none of which may lead to more accurate budget scores than under the CBO’s and JCT’s current approach.

In May, 2003, for example, the Joint Committee on Taxation (which scores tax legislation) provided a dynamic analysis of the House version of the tax cut legislation that was enacted in 2003. JCT used three different macro models with multiple sets of assumptions to come up with 5 different predictions of the budgetary impacts.

The JCT’s dynamic analysis found that the feedback effects would be deficit reducing and would reduce the net revenue loss from the proposed tax cut legislation relative to the conventional CBO estimate by anywhere from 5.8 to 27.5 percent over the first five years (2003—2008), and 2.6 to 23.4 percent over the next five years through 2013.

Now, nearly 12 years later, we can look back and accurately assess which of the scores was most accurate. It turns out that the most accurate was the conventional JCT score because all of the macro models failed to anticipate the great recession, and their revenue estimates were thus wildly optimistic and worse than the conventional estimate. To get an idea of how off-base the dynamic scores were, consider that they all expected GDP in 2013 to be larger than the roughly $17.9 trillion that the conventional score anticipated. Actual GDP in 2013 amounted to just $16.6 trillion, a difference of $1.3 trillion.

The lesson: macro models are still in their infancy. The large differences in their predictions are a function of both the different assumptions built into the models and the varying sensitivity of each model to those assumptions. Because we do not fully understand how the economy actually works, macro models are necessarily built on theoretical assumptions or educated guesses about the way the real economy works, many of which we know are sometimes not true and many others which have little hard data to back them up. Most macro models, for example, assume that the economy is typically at full employment or will quickly return to full employment. Neither has been the case for the past six years.

The macro models undergirding dynamic scoring have numerous controversial and unproven built-in assumptions
Most macro models assume that there are significant supply-side work incentive effects due to tax cuts. The argument goes like this—when given a tax cut, people will choose to work longer and harder thereby spurring economic growth. The theoretical basis for this assumption is that a tax cut increases the returns to working as workers can keep a larger share of their earnings, causing workers to substitute more work for leisure. But there is a plausible theoretical reason to assume the opposite: Tax cuts discourage work because they raise take home pay and enable workers to afford more leisure and less work.

Similarly, most macro models assume that tax cuts on income from investments spur more investment, faster economic growth, and job creation. But here too, theory leads to contradictory conclusions. A tax cut on returns to investment, such as a dividends tax cut, may, in theory, make investment more attractive and thereby induce additional investment and faster economic growth. Yet a tax cut that raises current and future investment yields may simply cause individuals to consume more and thereby save and invest less, slowing long-run economic growth and job creation.

The assumptions embedded in the macro models are not always carefully empirically based
Whatever the merits of these theoretical arguments, there are numerous studies that have tried to quantify these incentive effects in the real world and have come to contradictory conclusions about whether there are incentive or disincentive effects. Most of these studies conclude that the effects on incentives to work and invest due to tax cuts, whether positive or negative, are very small—much smaller than typically assumed in many macro models.

It is important to understand this particular theoretical and technical problem with macro models and dynamic scoring—they have embedded within them implicit or explicit supply-side behavioral responses, in terms of work effort and investment, to tax changes that are larger than can be justified by empirical evidence. In other words, these models typically assume larger changes in work effort and investment in response to tax changes than can be supported by a careful analysis of the data. This means that they could overstate the beneficial growth effects and subsequent positive feedback effects on budgets of tax cut proposals and exaggerate the detrimental effects on growth of tax increases.

In a recent careful comparison of the empirical estimates of supply-side responses to the estimates of supply-side responses embedded in eight of the most widely used macro models, including four models used by CBO or JCT, the Congressional Research Service finds that some models “make little attempt to connect the elasticities associated with labor supply to the ones found in empirical evidence.” Elasticities in economics parlance measures how one variable responds to another variable, such as how much work and investment change in response to a tax change. The Congressional Research Service also finds that some models had assumptions about the behavioral responses to taxes on investment income that were large, “unlikely and not empirically studied.”

Macro models exclude theoretically and empirically supported evidence of supply-side effects of public investment
At the same time as they include questionable assumptions about the supply-side effects of taxes, macro models generally exclude supply-side effects of government spending programs even when they can be supported theoretically and by empirical evidence. For instance, a public investment in infrastructure could lower business transportation costs and increase productivity, thereby making private investment more attractive. If so, then the public investment will induce more private investment, stimulate growth, and create jobs. A growing body of empirical research shows that public investment does indeed have a positive supply-side impact by inducing or “crowding-in” private investment.

This supply-side effect of public investment causes faster economic growth and leads to job creation. To the extent that macro models ignore this supply-side effect of public spending, they will understate the growth effects of government investment and the positive budgetary feedback effects that dynamic scoring, if done correctly, should be able to capture. In short, macro model estimates of economic outcomes are overly determined by their built-in supply-side assumptions, which are biased in favor of tax cuts and against spending increases.

Macro models exclude evidence-based effects of economic inequality
Then there are a host of assumptions for which we have evidence but which are not included in these models, sometimes because we do not know how to incorporate them into the models. There is growing evidence, for example, that high levels of economic inequality (such as those prevailing in the United States over the past few decades) slow economic growth.

Similarly, evidence is accumulating that tax cuts benefiting the wealthiest, such as business tax cuts and reductions in the top marginal personal income tax rates, contribute to income inequality. If this new research is correct, then tax cuts for the rich may contribute to income inequality and slow economic growth—exactly the opposite growth effect of what many macro models assume and predict. Macro models generally do not take these potentially negative effects of tax cuts into account.

Macro models exclude evidence-based effects of numerous policies
Even when the empirical evidence is overwhelming, macro models may ignore the data. Fifty years of careful research demonstrates that investments in high-quality early childhood education programs have enormous long-term payoffs in the form of faster economic growth. These investments partly or largely pay for themselves by generating faster growth, more earnings, and large increases in government revenues.

Similarly, there are well-documented positive growth-and-revenue effects of policies that raise academic achievement and narrow educational achievement gaps between children from wealthy families and other children. A new study that I wrote for the Washington Center for Equitable Growth documents these positive effects on our economic growth and federal fiscal health over the next 35 and 65 years. But look for those assumptions in a macro model and you will come up empty.

Macro models provide different estimates of growth impacts of policy depending on guesses of how the policy may be financed
To make matters worse, each macro models spits out different predictions about the growth effects of legislation depending on the assumptions fed into the model about how the legislation will be financed. All tax and spending proposals are financed and the financing methods affect the economy in differing ways. Consider a $100 billion tax cut proposal. Will the tax cut be paid for by cutting $100 billion in spending, raising $100 billion in other taxes, borrowing $100 billion, or some combination of all three? The fact is, we do not know today how legislation will be financed over time, but the financing method we input into a macro model will affect the model’s prediction for future economic growth.

If JCT guesses incorrectly how the tax cut will be financed in the future, then their dynamic score will necessarily be wrong even if the macro models they use are accurately constructed. That’s why it’s important to note that under conventional scoring there is no need for CBO or JCT to guess about future and unknowable congressional actions that will impact how much a current proposal will cost or save because a conventional score does not attempt to measure growth effects.

So, if we insist on dynamic scoring, which macro model, with which assumptions, will we use? Will we rely on those models whose assumptions give the most favorable answers, the least favorable answers, or something in between? Will that make budgeting more accurate? Or will it be more susceptible to manipulation and less accurate? Right now, the answers to these questions are highly debatable compared to the consensus surrounding the current conventional method of scoring used by CBO and JCT.

Dynamic scoring causes a coordination problem with standard government economic and budget forecasts
There is also a non-trivial coordination problem that arises when dynamic scoring is used under the new House rule. At present, CBO makes a series of budget and economic forecasts using baseline economic assumptions that are updated twice every year. If dynamic scoring is used to analyze certain pieces of legislation and the new proposals are deemed to have economic impacts, even very small ones, then to maintain the consistency and accuracy of the regular CBO forecasts the baseline economic assumptions would have to be updated every time those new proposals are passed into law. If the new House rule had been in effect in 2014, then it would have required the application of dynamic scoring to three proposals which, had they passed, would have necessitated a more than doubling of the number of annual baseline updates.

The new House rule is biased against pro-growth policy

Clearly there are good reasons to be concerned about the growth-undermining biases of dynamic scoring in the new House rule. Instead of correcting the anti-growth bias of conventional scoring, dynamic scoring may exacerbate the problem because the new House dynamic scoring proposal does not apply to discretionary spending, thereby ignoring potential growth effects of investments in many areas including in research, health, education, and infrastructure.

Consider a large tax cut proposal that benefits the wealthiest taxpayers and compare it to an equal-sized investment in infrastructure. Some of the latest empirically-based economic research suggests that the true growth effect of such a tax cut proposal may be negative. But, given the assumptions built into the macro models, under dynamic scoring it would likely be judged to have a pro-growth effect and cost less than the conventional score would suggest.

The infrastructure investment, by contrast, may have a positive impact on growth and may actually cost less than the tax cut proposal. But, by the conventional scoring that the pro-growth investment would be subject to under the new House rule the investment would be assumed to have no effect on growth and would thus be incorrectly judged to cost more than the equal-sized but dynamically scored, anti-growth tax cut proposal.

To make matters much worse, macroeconomic models that find growth effects of tax cuts often do so only when they make the assumption that tax cuts will be paid for in the future by reductions in government spending and further assume that these future reductions in government investment will have no negative impact on growth. Provided this budgetary misinformation, policymakers may vote for growth-retarding, growth-neutral, or relatively slow growth-promoting tax cut proposals over relatively faster growth-promoting investments.

Conclusion

Given the uncertainty and biases inherent in the assumptions undergirding currently existing macro models, it makes little sense to use dynamic scoring. But if we are going to use dynamic scoring, at minimum it should be done in an appropriate and balanced manner and applied to expenditure programs as well as tax proposals. Unfortunately, dynamic scoring of all proposed legislation is clearly not feasible because CBO and JCT do not have the time or resources to dynamically score all proposals. While there is a cost to doing dynamic scoring there may frequently be little benefit because for most legislation the macroeconomic effects would be small and uncertain, and the feedback effects on the budget would likely be negligible.

Indeed, arguably one of the best reasons to use accurate dynamic scoring would be to check the empirically unverified claims made by some Members of Congress that their pet legislative proposals would pay for themselves by boosting growth and subsequent revenues. But given the costly nature of dynamic scoring and the insignificant budgetary impacts of most proposed legislation, it should be restricted to analyzing the macroeconomic effects of only significant proposals—all significant policies, including spending proposals as well as tax proposals.

If dynamic scoring were done across the board for all significant tax and spending proposals using highly accurate macro models then thoughtful people should be for its use. But given the reality of unsophisticated and inaccurate macro modeling, built on less than thorough, rigorous, and evidence-based assumptions, and subject to biases and manipulation, we would do better to continue using the conservative, less expensive, and transparent conventional scoring method. The use of dynamic scoring given the current state of the art, may cause greater budgetary uncertainty and less accurate budget forecasts.

Perhaps most damaging, the new House rule may preclude careful evaluation of tax and spending proposals and lead to public policy distortions that will slow down long-run economic growth, weaken job creation, and undermine economic well–being.

—Robert G. Lynch is a visiting fellow at the Washington Center for Equitable Growth and the Everett E. Nuttle Professor of Economics at Washington College. His areas of specialization include human capital, public policy, public finance, and income inequality.

An appreciation of Robert Solow

Posted on November 24, 2014April 25, 2018 by Nick Bunker

President Obama today is awarding the Presidential Medal of Freedom to a number of accomplished Americans, including Robert Solow, Institute Professor, emeritus and Professor of Economics, emeritus at the Massachusetts Institute of Technology, Nobel Laureate in Economics, and a member of Equitable Growth’s Steering Committee

Robert Solow’s name is familiar to anyone who’s taken an introductory macroeconomics course. Solow’s model of economic growth is the first, and for the vast majority of students, the only growth model they will learn. And it’s for this work that Solow won the Nobel Prize in 1987.

The Solow growth model has one key takeaway: the source of long-term economic growth is technological growth. Before Solow’s 1956 and 1957 papers outlining the model, some economists believed that a country could boost its rate of economic growth by increasing its savings rate or adding more workers to its labor force.

But Solow’s model shows something else. Increasing the savings rate could get an economy to a higher level of output after the increase, but the long-run rate of economic growth wouldn’t increase. Doubling the savings rate would increase a country’s GDP per capita, but it wouldn’t change the fact that the economy would grow at the same rate as before. But a “technological” advance boosts the long-run growth rate of the economy.

Think of it this way: an increase in the savings rate moves an economy along a line, but technological growth shifts the line out.

Now by technology Solow’s model doesn’t mean just advances in computers or robots, but rather anything that allows for a more efficient use of capital and labor. In that way, technology is essentially the same thing as total factor productivity. What determines the growth in TFP over time is still very much an open question in economics.

But Solow’s model is important for guiding how we thinking about economic growth in the real world. For example, once you understand the Solow model you realize a country like China growing much faster than the United States isn’t so surprising. China is experiencing catch-up growth as it invests more in its economy and adopts technology and other resources from richer countries. Eventually China will catch up to the technological frontier and grow at about the same rate as the United States. At least in the long-run.

As for countries already at the frontier, the model indicates that the path to sustainable long-term economic growth is to improve productivity. Rich countries can help boost the productivity of labor by improving access to and the quality of education, increasing the productivity of capital by creating institutions that allocate it more efficiently, fostering innovation, or a variety of other policy options.

Solow’s most famous work is certainly theoretical, but it has clear policy implications. Solow himself delved more directly into the world of economic policy when he served in government. He served as a senior economist for the Council of Economic Advisers during the Kennedy Administration in the early 1960s.

Though Solow officially retired from MIT in 1995, he continues to engage in the economic and policy debates of the day. He wrote one of the best received reviews of Thomas Piketty’s Capital in the 21^st Century published in the New Republic. And he does not shy away from engaging in contentious debates.

The Presidential Medal of Freedom is awarded to individuals who make especially “meritorious contributions” to society. Robert Solow’s contributions certainly have great merit. Through his groundbreaking insights into economic growth, his government service, and his role in the public debate, Solow has helped create a more prosperous United States.

State-by-state minimum to median wage ratios

Posted on November 5, 2014April 18, 2018 by David Evans

The data

Under “Downloads”, to your right, you will find the data used to create the interactive “Where does your state’s minimum wage rank against the median wage?”. Please cite the Washington Center for Equitable Growth if you use the data.

Methodology

The state-level minimum-to-median wage ratio is the ratio of the average of the state minimum wage to the state’s median wage in that year. The median wage is the median hourly wage in the Outgoing Rotation Group of the Current Population Survey of earners who work at least 35 hours per week and who are not self-employed. The national minimum-to-median wage ratio is the population-weighted mean of state minimum wages divided by the median national wage.

A White Paper on Piketty’s Theory of Inequality and its Critics

Posted on September 2, 2014April 18, 2018 by Ed Paisley

In “Capital in the 21st Century,” Thomas Piketty of the Paris School of Economics proposes an economic theory of rising inequality over time thanks to the growing prevalence of capital over labor. That theory’s analysis of recent trends and its prediction about future inequality—and the capital-centered channel that he specifies for it to play out—have been subjected to criticism from economists, most pointedly from some who conduct research in macroeconomic theory. There are substantial differences between the theory Piketty uses and some of the economics profession’s received wisdom. This short paper examines how his theory relates to key ideas in macroeconomics, and, where they are not consistent with Piketty’s empirically-based analysis and conclusions, why Piketty’s assumptions, reasoning, and predictions are more likely to be correct than those of his critics.

Piketty argues that there are two mechanisms by which capital is and will continue to be the reason for rising wealth and income inequality. Both mechanisms are premised on the long-run empirical relation r > g, meaning that the rate of return to owning capital is higher than the economy-wide growth rate (which determines the growth rate of wages). Both mechanisms are also based on the empirical fact that the distribution of capital is highly skewed: the top 10 percent of the wealth distribution has always owned more than 50 percent of total wealth, and has historically owned 90 percent or more of total wealth.

The two mechanisms that determine rising wealth and income inequality are:

• The wealthy are likely to accumulate more and more wealth (as a percentage of the economy’s annual output) because the return they get from existing wealth net of consumption and of wealth taxes is higher than the growth rate of output. As they do, the share of annual output that accrues to the owners of capital will increase. That growing capital share increases the incomes of the already-wealthy owners of capital relative to the much larger portion of the population who earn income mostly or solely from their labor.

• Even stipulating that capital’s share of income remains constant, the wealth and income distributions can still become more and more skewed thanks to capital accumulation if the rate of return earned by the wealthy is an increasing function of initial wealth, or if the saving rate is an increasing function of initial wealth, or both.

Each of the three challenges considered in this white paper casts doubt on one or both elements of Piketty’s capital channel. (Please click here to read the full white paper and citations)

Designing a research agenda to move the minimum wage forward

Posted on July 24, 2014April 18, 2018 by Ed Paisley

During the most recent push to raise the federal minimum wage in the United States, more than 600 economists signed a letter encouraging Congress to do so, including seven Nobel laureates. This letter highlighted research that the minimum wage has little to no impact on the employment of minimum-wage workers and that a raise would provide a small stimulus effect on the economy. A few weeks later a letter opposing a rise in the minimum wage was released with the signatures of more than 500 economists, including three Nobel laureates. The opposing letter focused on the increase in labor costs and pointed to a Congressional Budget Office analysis that finds an increase would reduce overall employment, although the 90 percent confidence interval included a zero effect. These economists fundamentally disagree about the response of employment to minimum wage increases, contributing to the paralysis at the national level on the minimum wage, but both claim to point to “the research.”

Read a pdf of the full document.

We propose a series of research projects targeted at advancing the policy debate. In their February 2014 report the Congressional Budget Office highlighted several areas where they argued that there was not enough information or consensus to make strong assessments. We are reaching out to advocates and policymakers to better understand the questions about the minimum wage they want and need answered, with the intention of shaping a research agenda on the minimum wage that directly answers their questions.

Below we identify research questions that may be of interest to policymakers and advocates inspired by the existing academic research as well as the recent CBO paper. This discussion paper should be treated as the name implies—a jumping-off point for a conversation about a research agenda designed to move the policy process forward.

The 2014 Congressional Budget Office report, “The Effects of a Minimum-Wage Increase on Employment and Family Income,” addressed the questions posed to them by Congress on the impact of an increase in the minimum wage, and relied on the most up-to-date academic research in doing so.

Consequently, the CBO report had to adjudicate between a wide variety of studies on the minimum wage, not all of which pointed to the same conclusions. In many cases, the report splits the difference, such as when it cites “uncertainty about the responsiveness of employment to an increase in wages.” Given these inconsistencies, a minimum wage research agenda that addressed the following questions could help clarify and focus the empirical evidence:

How does the minimum wage affect production?
How do outputs, profits, and prices change?
Does a rise in the minimum change worker efficiency?
Do increases affect low- and high-productivity firms differently?
Are there changes to workforce composition or hours worked?
How does the minimum wage affect the overall wage distribution?
How large are“ripple effects”for workers who already earn more than the minimum wage?
How much does the minimum wage change income inequality?
Does the minimum wage affect the macroeconomy?
How much less is spent on government benefits for low-income people?
How do consumption patterns change from increased wages?
How does the structure of the minimum wage policy impact outcomes?
How do effects vary by the size of the minimum wage increase?
Do minimum wage changes have different short- and long-run effects?

Many of these questions have been addressed directly or indirectly in the economics literature, but work will be needed to synthesize and effectively communicate the results in a way that allow for a more direct, effective response to CBO’s analysis. Yet many
of these topics are under-researched or rely on older data, suggesting a need for new research. This discussion paper explores several of these questions as a starting point for encouraging new research.

How do employment effects vary by the size of the minimum wage increase?

While recent research suggests that modest increases in the minimum have strong effects on earnings and small effects on employment, little work exists on whether this pattern holds for larger raises. Economic theory suggests that the effects will vary by the “bite” of the minimum wage into the underlying wage or productivity distribution. In a study of the 1996 and 1997 federal minimum wage changes, Economist Jeffrey P. Thompson— now at the Federal Reserve Board and previously a professor at the University of Massachusetts, Amherst, found that in 2009, counties with low average earnings (where the minimum’s “bite” was greater) had larger falls in employment after the wage change. Offering an international perspective on the debate, economists Yi Huang, Prakash Loungani, and Gewei Wang estimated that after China strengthened minimum wage enforcement, firms with low profit margins reduced employment, but firms with high profit margins expanded.

Seattle has just passed legislation to increase the city minimum wage from $9.32 per hour today to $15 by 2017-2021, depending on the type of employer. San Francisco is now con- sidering following suit. Opponents of the minimum wage frequently respond by highlight- ing the arbitrariness of the levels proposed by legislators. Additional research could ground the levels in analysis and help policymakers identify the best targets.

Do minimum wage changes have different short-run and long-run effects?

In his review of the research fifteen years ago, University of Michigan economist Charles Brown emphasized that understanding the long-run effects of the minimum wage remains “the largest and most important gap in the literature.” Perhaps the research overall found no short-term employment effects because firms are unable to modify production in response to a minimum wage increase in the short-run, but in the medium- to long-run, they are less constrained in terms of hiring patterns and substituting capital for labor.

More recently, Texas A&M University economists Jonathan Meer and Jeremy West argued that the minimum wage primarily influences employment growth, rather than the employment level. Therefore, an increase in the minimum wage has a small effect on employment levels in the short-run , but a large effect in the long-run. In contrast, economists Arindrajit Dube at the University of Massachusetts, Amherst, T. William Lester at the University of North Carolina, Chapel Hill, and Michael Reich at the University of California, Berkeley, failed to find effects on employment levels up to four years after minimum wage increases. Additional work must reconcile conflicting evidence on long-term effects of an increase in the minimum wage.

How does the minimum wage affect production?

To respond to a minimum wage increase, employers and workers may choose a variety of “channels of adjustment,” such as raising prices or improving efficiency. The most comprehensive evidence suggests that restaurants raise prices in response to a minimum wage increase, passing a portion of increased labor costs onto consumers. Unfortunately, the city-level data used in this analysis is almost two decades old, and has not been subjected to alternative specifications. With more recent but less comprehensive data, economists Emek Basker and Muhammad Khan at the University of Missouri, Columbia, find similar price increases for two out of three restaurant items. New research with better quality price data has a high probability of informing how much affected businesses raise prices after a minimum wage increase.

By improving worker and managerial efficiency, minimum wage increases may boost labor productivity. Productivity effects would be consistent with current research confirming that worker turnover falls sharply after a minimum wage increase, both in the United States and Canada. In addition, restaurant managers’ survey responses suggest that minimum wage increases provide an opportunity to portray the “cost shock as ‘a challenge to the store’” in order “energize employees and to improve productivity,” according to a study by economists Barry Hirsch and Bruce Kaufman at Georgia State University. Similarly, using plant-level data in the United Kingdom, economists at the National Bureau of Economic Research find that revenue-per-worker increases in response to a minimum wage rise, but the effect is statistically insignificant.

Firms may also adjust production practices in the face of a minimum wage increase by hiring more highly skilled workers, or by reducing hours of the lower-skilled work- force. Existing high-quality studies do not generally find large effects on workforce composition and hours, but the estimates remain too statistically imprecise to rule out substantive effects. One recent study, for example, estimates that teen hours either fall somewhat or not much at all, depending on the specification.

More recent but preliminary work suggests that relatively small employment-level impacts of the minimum wage may conceal large changes in the mix of firms. The study finds that restaurants in three states that raised minimum wages during the 2000s experienced increases in employees’ hiring and departures from firms. New research must provide more comprehensive and precise evidence on how firm composition and output change in response to the minimum wage.

How does the minimum wage affect the overall wage distribution?

By raising the wage floor, the minimum wage reduces inequality, but current research has not settled on the size of these effects. One study in 1999 estimated that the falling real value of the minimum wage accounted for the entire increase in wage inequality between the median wage and the 10th percentile wage during 1979-1989. In contrast, a new study this year by economists David Autor and Christopher L. Smith at the Massachusetts Institute of Technology and Alan Manning at the London School of Economics finds that the falling real minimum wage accounted for about one-third of the inequality increase. Better data quality and more recent empirical techniques can improve estimates of the minimum wage’s impact on inequality.

In raising the minimum wage, workers just above the minimum wage will often see a wage increase. While many studies observe these “ripple effects” or wage spillovers, existing empirical work does not evaluate any underlying mechanisms. Do the spillovers occur within firms, as workers paid just above the minimum also demand raises? Or do they occur in the market, as firms are forced to raise wages to attract new workers? Or do they occur as employers attempt to maintain established wage structures (internal pay scales) within firms?

What are the macroeconomic effects of the minimum wage?

By lifting workers out of poverty, the minimum wage may reduce fiscal spending on income support and welfare programs. Two economists at the Institute for Research on Labor and Employment, Rachel West and Michael Reich, find that the minimum reduces the use of food stamps as well as state-level expenditures on that program. Additional empirical work could examine other needs-based programs and quantify state-level budget impacts.

Minimum wage raises likely translate into increased consumption, but little work exists
on directly measuring these effects. One recent study finds a minimum wage change leads to large increases in consumption; these expenditures seem concentrated in automobile purchases partially financed by debt. New research with high quality individual-level data will help to improve estimates of the consumption response to minimum wages.

A final related issue is whether minimum wage increases affect the economy differently during times of economic slack or expansion. One recent study finds that the minimum has large negative effects on employment when unemployment is high, but another one finds no such evidence. More work is needed to identify credible estimates of how the minimum wage interacts with the broader economy.

Who are today’s supermanagers and why are they so wealthy?

Posted on July 16, 2014April 18, 2018 by Ed Paisley

What explains the changes in top-earning occupations over the past four decades? Perhaps the most intriguing argument about the current state of income inequality in the English speaking economies that Thomas Piketty makes in his bestseller “Capital in the 21^st Century” is this—“the vast majority (60 to 70 percent, depending on what definitions one chooses) of the top 0.1 percent of the income hierarchy in 2000-2010 consists of top managers.” He goes on to argue on page 302 of his book that the rise in labor income “primarily reflects the advent of ‘supermanagers,’ that is, top executives of large firms who have managed to obtain extremely high, historically unprecedented compensation packages for their labor.”

This really begs the question as to how and why these supermanagers came into existence. Nobel Laureate Robert M. Solow points out in The New Republic that this is primarily an American outcome. And Henry Engler at Thomson Reuters Accelelus’ Compliance Complete recently published an excellent piece on Piketty’s supermanagers in the United States and the United Kingdom. Both writers agreed with Piketty that these supermanagers were being vastly overly compensated given their questionable contributions to productivity.

I hope to shed a little more light on this issue by examining the change in professions comprising the top 0.1 percent of tax filers between 1979 and 2005. The purpose: to examine whether the changing composition of this super elite reflects changes in our economy that may explain the link between rising economic inequality and anemic economic growth over this period.

To do so, I used data from the April 2012 white paper “Jobs and Income Growth of Top Earners and the Causes of Changing Income Inequality: Evidence from U.S. Tax Return Data,” by economists Jon Bakija of Williams College, Adam Cole of the Office of Tax Analysis at the U.S. Department of the Treasury, and Bradley Heim of Indiana University. They used tax data on the top 0.1% of filers to identify the top earning professions. The infographic below tells the tale, charting the change in occupations at the tippy top of the income ladder in 1979 and 2005.

The biggest change in the distribution of top earners is in the types of executives, managers, and supervisors at non-financial firms. In 1979, most of these people worked for large, publicly traded firms but by 2005 more were working in closely held firms. There is not enough information to provide a clearer picture as to who exactly these people are, but chances are they are employed by firms that are owned by private equity firms—the growth in the private equity industry over this period of time was substantial—and because financial professionals saw large gains, too. The share of people in the top 0.1 percent working in finance also increased substantially, to 18 percent in 2005 from 11 percent in 1979.

These findings are consistent with Piketty’s analysis in his new book. But there are alternative explanations. One is presented in George Mason economist Tyler Cowen’s latest book, “Average is Over.” He claims a skill biased-technological change is responsible for the shift in top occupations over roughly the same period. He argues that technology allows top performers to capture more of the market and thus earn substantially more than average performers. He and many other people hypothesize that this is a driver of increased economic inequality.

But if technology were a primary driver of inequality, then one would expect that skilled trades would have larger incomes and would have become a larger share in the top 0.1 percent. While there are slightly more technical types and entertainers among top earners (as can be seen in the data presented in our interactive) the biggest gains in both percentage terms and magnitude were among privately held business professionals.

Thus, the so called “average is over” argument—that that the top performers in each field will capture a bigger share of the pie—may be a driver of inequality, but it does not appear to explain the bulk of the changes in occupations at the top of the income ladder. Instead, the supermanagers appear to be capturing greater share of the wealth as is argued by Piketty and others. More detailed data would be required to assess who these people are and how workplace dynamics changed from 1979 to 2005 that would explain the change in income. The Washington Center for Equitable Growth will be examining this data in more detail in forthcoming publications.

Missing the Point on Income Inequality in the 1920s and Today

Posted on June 3, 2014April 18, 2018 by Ed Paisley

Gary Burtless of the Brookings Institution takes issue with widely publicized findings that income inequality in the United States has reached the level that prevailed in the 1920s, when the top one percent of earners received 20 percent of total income. According to Burtless, that conclusion ignores the creation of the welfare state, consisting of Social Security, Medicare, Medicaid, and other government programs that aim to redistribute disposable income and goods and services to Americans in retirement and those at or near the poverty line. These programs did not exist in the 1920s, argues Burtless, so to ignore them is to misrepresent the degree of income inequality today. Columnist Robert J. Samuelson made the same argument in a column yesterday.

In support of that argument, Burtless turns to the Congressional Budget Office, which calculates measures of pre-tax-and-transfer “market” income, post-transfer income, and post-tax-and-transfer income. Specifically, Burtless turns to a report CBO published breaking down income in 2010. That report does show that taxes and transfers redistribute income relative to “the market,” meaning gross household income from labor, capital, rent, royalties, and miscellaneous non-government sources.

But this CBO analysis doesn’t provide crucial context—the extent to which the redistribution of income through tax policies and government spending has declined since 1979. I discussed this last week, largely in reference to an earlier CBO report that explicitly tracks the trends in pre- and post-tax-and-transfer income distributions. The data needed for that analysis doesn’t extend back to the 1920s, but Burtless is likely correct that since there was far less in the way of redistributive government policy back then, the post-tax-and-transfer distribution then was more stratified than it is now.

But this line of argument neglects that between the 1920s and today income became much less stratified, thanks to higher effective taxes on the very wealthy that helped pay for the New Deal and Great Society progressive programs enacted in the interim—policies that resulted in sustained and stable economic growth, unlike what prevailed before or after. Since the advent of supply side economics in the 1980s, of course, tax policies have become less redistributive in percentage terms exactly as market income has become more unequal, and transfer programs have shifted their focus toward the elderly of all income levels and away from the poor.

The upshot: the potential for policies to rectify income inequality and boost economic growth is very high, which by itself invalidates long-term conservative arguments that government is powerless or ineffective in the face of “the market’s” inexorable force. Burtless’ claim is correct, but some conservative critics of the latest research on income inequality are using the welfare state they previously devoted themselves to dismantling to support their argument that inequality either doesn’t really exist or is at least not as bad as in the 1920s.

The aftermath of wage collusion in Silicon Valley

Posted on May 27, 2014April 18, 2018 by Carter Price

The settlement is in—some of Silicon Valley’s biggest and most influential technology companies late last week agreed to pay $324.5 million to settle a class-action law suit brought by their employees alleging collusion to suppress their wages. After an anti-trust investigation, the U.S. Department of Justice filed a complaint in September of 2010. The companies eventually settled with the department and stopped the practice. The targeted workers and the companies involved agreed to settle last month, with the amount announced last week.

But will there be any repercussions from this long legal tangle between employers and employees in one of the leading industries in the country? A great series of stories on Pando Daily lay bare the alleged efforts of big tech companies (including Apple Inc., Intel Corp., and Google Inc.) for a secret “do not hire” cartel deterring these companies from hiring each other’s workers, which artificially suppressed their workers’ wages. In the mid-2000s there was a high demand for programmers and engineers, which pushed up their wages. To combat higher pay, Apple’s Steve Jobs and Google’s Eric Schmidt allegedly agreed to stop trying to hire each other’s workers, using their size to pressure other firms to join them.

Yet some conservative economists, among them George Mason University economics professor Tyler Cowen on his popular Marginal Revolution blog, argue this kind of cartel is not terribly important because some firms will cheat, causing the system to fall apart, while new workers will figure out that there is a cartel and go work somewhere else for more money. But this particular case of wage collusion lasted from 2005 to 2009 and took the Justice Department to solve this problem, not the market.

In fact, this series of cases fit in with the narrative of French economist Thomas Piketty and his book “Capital in the 21^st Century.” Piketty describes some of the fundamental economic problems facing the developed world, emphasizing those related to earnings from work versus investment. Piketty’s conservative critics make much of the fact that the author targets the “supermanagers” of companies as culprits in the rise in income inequality in the developed economies, in particular the United States. On the editorial pages of The Wall Street Journal, for example, columnist Holman Jenkins argues that Piketty wants to pitchfork the idle rich but “somewhat disconsolately for his story, the U.S. has exhibited the wrong kind of income inequality, caused not by rising inheritances but soaring “labor earnings” of the managerial class, which he attributes to self-dealing by executives and boards. “

Piketty does discuss at length such self-dealing, mostly in order to note that labor earnings in the C-suite do not seem at all connected to any corresponding productively gains compared to these supermanagers’ steely-eyed focus on wages and productivity among their companies’ workforces. And now comes along a legal settlement in Silicon Valley that proves Piketty’s point in spades.

There are at least three concrete steps that can be taken to help combat future abuses. The first is to improve access to salary information. The Bureau of Labor Statistics provides some information about salary norms by occupation and location. More important are websites such as Glass Door that encourage people to share salary information. As participation increases, there will be less room for wage discrimination not just from executive to employees but also by sex, race, and ethnicity. Earlier this year, President Obama signed an executive order preventing federal contractors from discouraging workers from talking about pay. Legislation could expand this to protect all workers.

The second is to bring new analytic tools to investigating business collusion charges. Law enforcement and intelligence agencies have brought a wide array of new analytic tools to bear on problems of terrorism. White-collar crimes need the same rigor. The financial crisis was extraordinarily costly for not just the United States but the whole world, yet we spend only a miniscule fraction of the resources fighting business crimes as we do on national defense.

And third, policymakers could change the penalties to target the actual offenders, in this case, the colluding executives. Lawmakers could ensure that these rogue executives get stiff fines and even jail time. Firms can also act by using clawback provisions to recoup losses from fines. These actions would help deter future collusion.

In the aftermath of wage collusion in Silicon Valley, these suits and settlements highlight the need to modernize our systems to detect and deter such labor abuses, which are a problem for white collar workers, too.

Carter Price is a Senior Mathematician focusing on quantitative analysis of U.S. economic policy at the Washington Center for Equitable Growth.

Economic inequality and the parenting time divide

Posted on May 26, 2014April 18, 2018 by Ariel Kalil

Members of Congress across the political spectrum agree with the Obama administration on the importance of a quality education for all of our nation’s children. Indeed, there may well be a bipartisan consensus in Washington that all children, including low- and moderate-income ones, should have access to pre-kindergarten. Certainly academic research demonstrates that high quality education programs for young children are associated with improved outcomes later in life—even decades later—which is why growing up in a low-income family often consigns those kids to being low-wage earners when they grow up.

But learning in fact begins at home at a very early age and remains fundamental to success through high school. To break the cycle of economic disadvantage, we must consider the evidence on inequality and parenting. When we talk about economic inequality, we should remember how current conditions are likely to exacerbate inequality for future generations given the key role family plays in the intergenerational transmission of economic status. Few people believe that there should be complete independence between parents’ and children’s economic success, but in the race to the top, new research shows highly-educated families are at an ever-greater advantage.

Economists, psychologists, and others who study children’s achievement and well-being often talk about investments that parents make in their children—both money and time—the myriad things parents do to help their children develop successfully and reach their full potential. But researchers have not until recently thought about parents’ time investments in children as a mechanism for the intergenerational transmission of economic status. Yet we know that the amount of parents’ time spent talking, playing, reading, helping with homework, facilitating positive interactions with peers and other adults, and exploring the outside world are all important ingredients of parenting that help to ensure children’s development and long-term prospects.

We are learning more about how parents across the income spectrum spend their time with their children. The economist Jonathan Guryan and his colleagues used data from national time diaries to show that mothers with a college education or greater spend roughly 4.5 hours more per week directly interacting with their children than mothers with a high school degree or less. This relationship is noteworthy because higher-educated parents also spend more time working outside the home.

Interestingly, based on mothers’ patterns of time use across a variety of activities, these researchers posited that highly educated parents, more so than less-educated parents, view time with children as an investment behavior with which to increase children’s human capital. My own national time use research, with Professor Rebecca Ryan and one of our students, Michael Corey, finds evidence for this. Highly educated parents not only spend more time with their children than do less-educated parents, they spend that time differently. College-educated mothers are more efficient in their parental time investments by tailoring specific activities to children’s developmental stage.

In other words, highly educated mothers shift the composition of their time as the child grows in ways that adapt to children’s development at different developmental stages. When children are in preschool, for example, college-educated mothers focus their time with children on reading and problem solving. This is precisely when time spent in learning activities best prepare children for school entry. During the middle school years, college-educated parents shift their attention to the management of children’s life outside the home – at precisely the ages when parental management is a key, developmentally appropriate input.

Research indicates that non-college educated parents do not match their time investments to children’s developmental stage in this fashion. To the extent that highly educated parents increasingly adopt these patterns of investing in their children, the destinies of the children of college-educated parents may diverge even farther from those of their less-advantaged peers.

We still don’t know precisely why these patterns have emerged. It is possible that mothers learn about child development during college—such that highly educated mothers are consciously acting on knowledge attained in formal schooling. But college-educated mothers are also more likely to have higher incomes, to be married, and to have spouses who are more involved in child rearing; they may also have more flexible work schedules due their different types of employment. Unlike less-educated mothers, they can marshal all of these resources to help their children explore their full potential.

Regardless of the reason, we do know there are many direct and indirect policy measures to help support families and promote more equal access to opportunities for children. This why Congress and the Obama administration need to keep their eye on what matters for children and how we can support parents from all kinds of families be the best parents they can be. From providing access to high-quality education and health care for all children, to helping ensure parents who work can rise above poverty, as a society, we must consider our role in supporting every child’s ability to reach his or her full potential.

Ariel Kalil is a Professor in the Harris School of Public Policy at the University of Chicago, where she directs the Center for Human Potential and Public Policy.

“Expanding Economic Opportunity for Women and Families”

Posted on May 13, 2014April 18, 2018 by Ed Paisley

Heather Boushey, Executive Director and Chief Economist, Washington Center for Equitable Growth, testifying before the U.S. Senate Budget Committee on “Expanding Economic Opportunity for Women and Families”

Enabling Women to Succeed Builds Strong Families and a Growing Economy

I would like to thank Chairman Murray, Ranking Member Sessions, and the rest of the Committee for inviting me here today to testify.

My name is Heather Boushey and I am Executive Director and Chief Economist of the Washington Center for Equitable Growth. The Center is a new project devoted to understanding what grows our economy, with a particular emphasis on understanding whether and how rising levels of economic inequality affect economic growth and stability.

It is an honor to be invited here today to discuss how working women are critical for economic growth, and how federal policy can further advance women’s economic progress. My testimony today highlights the many aspects of our economy where gender inequality and economic inequality go hand in hand—to the detriment of many families and our nation’s economy—and also where economic inequality among women threatens family well-being and economic growth. Government policies can address these gaps in order to help women succeed, so our economy can succeed.

There are three takeaways from my testimony:

Women, their families, and the economy have greatly benefited from women’s entry into the labor force.
Yet there are barriers to women’s work that manifest themselves differently across the income distribution, which means that not all women realize their full economic potential.
There are a variety of ways that federal policy can encourage women’s labor force participation, among them tax credits and early childhood education programs, which provide critical support for low-income workers and working families. Federal policies such as pay equity and flexible work-family policies can grow our economy by encouraging greater labor force participation among women and increasing women’s contributions to family income.

Women’s employment is critical for families and the economy

Women’s entry into the labor force is one of the most important transformations to our labor force in recent decades. Between 1970 and 2000, the share of women in the labor force steadily increased, from 43.3 percent to 59.9 percent.[i] Today, most women work full time. Before the Great Recession in 2007, the share of women who worked 35 hours or more per week was 75.3 percent.[ii]

Women’s movement into the labor force also transformed how they spend their days, which is increasingly important for families’ economic wellbeing. About two-thirds of mothers are family breadwinners—those bringing home all of the family’s earnings or at least as much as their partners—or co-breadwinners—those bringing home at least one-quarter of their families’ earnings.[iii] Between 1967 and 2007, the most recent economic peak, the share of mothers who were breadwinners or co-breadwinners rose from 27.7 percent to 62.8 percent, and has increased slightly since then as the economic recession wore on.[iv] (See Figure 1.)

Figure 1. Share of mothers who are breadwinners or co-breadwinners, 1967 to 2010

Figure source: Sarah Jane Glynn, The New Breadwinners: 2010 Update (Washington, DC: Center for American Progress, 2012).

Women’s increased work is important for family incomes and for economic growth. In a paper we released last month, my colleagues Eileen Appelbaum, John Schmitt and I find that between 1979 and 2012, our nation’s gross domestic product increased by almost 11 percent due to women’s changed employment patterns.[v] This translates to about $1.7 trillion in output in today’s dollars. We find that women’s economic contribution is roughly equivalent to U.S. spending on Social Security, Medicare, and Medicaid in 2012.[vi]

Continuing women’s economic progress

Over the past four decades, women have made great economic gains, but more can be done to help women realize their full economic potential. Gender inequality in the workforce still persists between men and women. Additionally, while some women have made great gains in the workforce, too many women are being left behind.

Between 1960 and 2000, women’s labor force participation steadily grew and the gender pay gap steadily shrank. But progress has stalled for more than a decade. The share of women in the labor force has not significantly increased since 2000, hovering a bit below 60 percent.[vii] Similarly, in 2012 the female-to-male earnings ratio remained at about 77 percent, the same as in 2002.[viii]

To be sure, some women have pulled ahead and experienced increases in incomes despite the recent slow-down in women’s entry in the workforce. But not all women have experienced these gains. Between 2000 and 2007, for example, higher-wage women saw their real wages increase by four times the amount of women with poorly paid jobs.[ix]

One reason is that while some women have made progress entering into professional or male-dominated occupations, many women continue to work in female-dominated occupations that still pay low wages. In 2012, 43.6 percent of women worked in just 20 types of jobs, among them secretary, nurse, teacher, and salesperson. (See Table 1.)

Table 1. Top 20 occupations for women and men, 2012

Women across the wage distribution need more access to work-family policies in order to better balance the dual demands of work and home. Polices such as paid sick days, paid family leave, and schedule flexibility would fill an important inequality gap for workers, especially women. This basket of work-family policies would allow both women and men to remain in the labor force while dealing with life’s emergencies.

The United States is an outlier among other developed nations in not offering work-family policies to workers.[x] Nor have employers in our country stepped in to provide these benefits. In 2013, only 61 percent of workers had employer-provided paid sick days.[xi] An even smaller share of workers—only 12 percent—had access to employer-provided paid leave, which can be used to recover from an illness or care for a family member.[xii]

Despite playing a larger role as family breadwinners, women today continue to be more likely than men to provide care to their families. The lack of family friendly policies make it harder for women to stay employed and provide financially for their families. Women who have to quit their jobs in order to provide care harm their future earnings potential. The U.S. Census Bureau found that new mothers who have access to paid maternity leave are more likely to return to their previous employer. About 98 percent of those who return to the same employer do so at their previous pay level or higher. Conversely, less than 70 percent of women who change employers after giving birth earn the same level of pay or higher.[xiii]

Work-family policies are critical for the strength and size of our labor force. In a 2013 study by Cornell University economists Francine D. Blau and Lawrence M. Kahn, the authors argue that likely one reason why the United States fell from the sixth-highest female labor-force participation rate among 22 Organisation for Economic Co-operation and Development countries in 1990 to the 17th-highest rate in 2010 was because it failed to keep up with other nations and adopt family-friendly policies.[xiv]

Although most workers do not have access to these important policies, low-wage workers disproportionately lack access to policies to balance work and care. Employers often view policies such as paid leave or paid sick days as perks for higher-paid workers. Too often workers who need these benefits the most—such as low- and middle-wage, young, and less-educated workers—do not have access to them. Workers whose wages are in the lowest 25 percent of average wages are approximately four times less likely to have access to paid family and medical leave than those in the highest 25 percent.[xv]

The lack of benefits for women earning the least in our economy is unhealthy for their families, the labor force, and the economy. Poorly paid jobs that do not provide these work-family benefits often offer nonstandard work or varying schedules, which often result in high employee turnover.[xvi] There is more we can do to boost women’s economic progress, and thereby boost the strength of the entire economy.

Federal policy can help working women succeed

Federal policies can encourage women’s work and increase family income. Specifically, these six policies are tailored to achieve the results we need for our families and our economy:

The Earned Income Tax Credit, Child Tax Credit, and Child and Dependent Care Tax Credit
The 21^st Century Work Tax Act
Broader and less expensive access to child care and early childhood education programs
Work-family policies, such as family and medical leave insurance, as proposed in the Family and Medical Insurance Leave Act
Pay equity
Raising the minimum wage

Let’s examine each of these policies briefly in more detail.

Tax credits

With most working women playing the dual roles of breadwinner and caregiver, tax credits can help increase the financial security of American families. The Earned Income Tax Credit is a fully refundable tax credit for low-income working families. The credit is larger for those with dependent children.[xvii] The Earned Income Tax Credit is an effective anti-poverty policy that encourages work, especially among low-income single mothers.[xviii] In 2012, this tax credit lifted 6.5 million people out of poverty, according to the Center on Budget and Policy Priorities.[xix]

Additionally, there are two other tax credits that help most working families—rather than just low-income families—offset the cost of raising children. The Child Tax Credit refunds families up to $1,000 per year, per eligible child.[xx] The Child and Dependent Care Tax Credit refunds families a percentage of total child-care costs, usually 20 percent to 35 percent.[xxi] The percentage of expenses refunded to families decreases as income rises. However, unlike the Earned Income Tax Credit or Child Tax Credit, this tax credit is not refundable, which means that only families who owe income taxes can benefit from the credit.[xxii]

Tax credits can benefit both our current and our future workforce. Tax credits provide families with additional income that can be spent on children’s skill development. For example, economist Gordon B. Dahl at the University of California-San Diego and economist Lance Lochner at the University of Western Ontario find evidence that increases in family income due to the Earned Income Tax Credit increase children’s math and reading test scores.[xxiii]

The 21^st Century Worker Tax Act

The 21^st Century Worker Tax Cut Act, introduced by Chairman Murray, would help promote women’s economic progress in two ways. First, the act proposes a new tax cut that would let low- and middle-income two-earner families keep more of what they earn. The tax cut would provide a 20 percent deduction on a secondary earner’s income.[xxiv] Furthermore, it would provide an additional benefit to low-income two-earner families. The 20 percent deduction would reduce their earned income for calculating the Earned Income Tax Credit and thus provide a higher refundable benefit.[xxv]

This deduction will benefit working mothers and their families in two ways. By deducting a portion of the secondary earner’s income, the cut would encourage mothers’ workforce participation, thereby helping them to better financially support their families. And it would help low-income working mothers offset the costs of child care through an enhanced refundable Earned Income Tax Credit. This would again further encourage mothers’ workforce participation and boost family income. It is estimated that the tax cut would benefit 7.3 million working families.[xxvi]

Second, the 21^st Century Worker Act also would help support childless working women. The Act would increase the Earned Income Tax Credit for childless workers to about $1,400 in 2015.[xxvii] Furthermore, it would increase income eligibility and expand the eligibility age for childless workers so more would be eligible for this tax credit.[xxviii] It is estimated that the Act would benefit 13 million childless workers.[xxix] With women making up nearly two-thirds of minimum wage workers,[xxx] this expansion would increase the financial security of low-income women, and provide them with a better shot at the middle class.

Child care

In order to work and remain in the labor force, mothers need affordable high-quality child care. As mentioned earlier, tax credits help families manage their child care expenses, but child care remains very expensive for most families. In 2011, the average cost for a 4-year old in center-based care ranged from less than $4,000 a year to more than $15,000 a year.[xxxi] With most working women earning less than $30,000 a year, many cannot afford care or spend a large portion of their earnings on care.[xxxii]

In addition to making child care less expensive, policy should address so called “child care cliffs” for families receiving child-care assistance. In certain states, a slight increase in parent’s earnings can push them over the income threshold for child-care assistance, which can result in a sharp increase in child care expenses.[xxxiii] Unable to pay for high-quality care, working mothers could turn down a raise or ask for a pay cut to avoid going over the “cliff.”[xxxiv]

Early childhood education is one of the most important investments in our future workforce. But not all child care meets the standards to be considered an early childhood education program. It is important that policies expand access to high-quality early childhood education programs, especially to low-income children. Research finds that children who participate in early childhood education programs are more likely to do better in school, graduate and attend college, and are less likely to get involved with crime and become teenage parents.[xxxv] There are also large benefits to society. An academic study found that for every $1 invested in high-quality preschool, the U.S. economy saves $7 in future public costs due to increases in workers’ productivity, reduced remedial education costs, and reduced crime.[xxxvi]

Head Start

The Bipartisan Budget Act of 2013, also known as the Murray-Ryan Budget Agreement, made important steps toward expanding early childhood education programs to working families. The Act provided about $8.6 billion in Head Start funding and for the President’s Early Head Start-Child Care Partnerships. This amount reversed the entire sequester cut to Head Start, about a half billion more than 2013 funding.[xxxvii] In fiscal year 2014, more low-income families can utilize this comprehensive early childhood program. About 57,000 children were dropped from the program in 2013.[xxxviii]

Family and Medical Leave Insurance

Women need polices to help them balance work and family care so they can remain in the workforce and help grow our economy. Family and medical leave insurance—also known as paid leave—would provide a critical support for workers—men and women alike—allowing them to take temporary leave from work to recover form an illness or care for a loved one.

The Family and Medical Insurance Leave Act of 2013, also known as the FAMILY Act, would relieve the financial burden of taking unpaid time off, providing paid leave for nearly every U.S. worker.[xxxix] Introduced by Representative Rosa DeLauro and Senator Kirsten Gillibrand, the FAMILY Act draws on what we have learned from states that have family leave insurance and from other federal benefit programs.

Today, only three states provide paid leave to their workers: California, New Jersey, and Rhode Island.[xl] These three states provide years of useful experience to other states interested in providing paid leave to their workers. To encourage states to offer paid leave programs, the President’s Fiscal Year 2015 budget requests a $5 million State Paid Leave Fund.[xli]

Paid leave makes it easier for women to work and have higher lifetime earnings. Research by economist Christopher J. Ruhm at the University of Virginia and researcher Jackqueline L. Teague find that paid parental leave policies are associated with higher employment-to-population ratios and decreased unemployment for all workers.[xlii] Ruhm and Teague also find that moderate leaves—10 weeks to 25 weeks—are associated with higher labor-force participation rates for women.[xliii]

By remaining in the labor force, women are able to earn more during their careers, increasing families’ financial security.[xliv] Furthermore, there is evidence that these work-family policies could also help close the wage gap between workers who provide care and those who do not.[xlv]

Pay equity

The pay gap today persists for all women. On average, working women only make 77 cents for every dollar earned by men.[xlvi] This gap means that women make $11,084 less than men per year in median earnings.[xlvii] If women were paid the same amount as their male counterparts, their additional earnings could help improve their families’ financial security as well as provide additional tax revenue to the government.

Making sure that women receive equal pay for equal work not only affects their lifetime earnings but also strengthens the economy. The Institute for Women’s Policy Research finds that if women had received pay equal to their male counterparts in 2012, the U.S. economy would have produced $447.6 billion in additional income.[xlviii] This is equal to 2.9 percent of 2012 gross domestic product, or about equal to the entire economy of the state of Virginia.[xlix]

The President’s Fiscal Year 2015 budget requests $1.1 million to help eliminate pay discrimination among federal contractors. The funds would be used by the Office of Federal Contract Compliance Programs to strengthen enforcement efforts.[l]

Minimum wage

Raising the minimum wage is critical for closing the wage gap. Low-wage workers are disproportionately women. Nearly two-thirds of minimum wage workers are women.[li]

Raising the minimum wage would provide many women—who represent 49.2 percent of total U.S. employment[lii]—with the economic security they need to succeed. According to calculations from the Economic Policy Institute, approximately 28 million workers would see a raise if the minimum wage were raised to $10.10 by July 2016.[liii] Fifty-five percent of the affected workers would be women. This share varies by state, and is as high as 63.3 percent in Mississippi.[liv]

Conclusion

Women’s employment is critical to their families and to our nation’s economy. Federal policy can do more to help women realize their full economic potential no matter where they are on the income ladder.

The Murray-Ryan Budget agreement has helped promote women’s economic progress in the workforce, but there will be more work to do after the deal expires.

We need to preserve tax credits such as the Earned Income Tax Credit and funding for early childhood education programs such as Head Start. Women are more likely to be low-wage workers, which means they and their families are more vulnerable to spending cuts. Passing the 21^st Century Worker Tax Cut Act would provide two critical tax credits to low-wage working women, helping increase their earnings and give them a better shot at entering the middle class.

In addition, ensuring pay equity and providing work-family supports such as the FAMILY Act to all working women will further their economic progress. Closing the wage gap and raising the minimum wage boosts women’s earnings and could generate additional tax revenue. Work-family policies help breadwinner mothers remain in the labor force and better financially provide for their families.

As a critical driver of economic growth, women need polices that expand workforce opportunities. Yet to help all women succeed, polices must acknowledge that barriers to women’s work manifest themselves differently across the income distribution. To echo House Minority Leader Nancy Pelosi, “when [all] women succeed, America succeeds.”[lv]

Endnotes

[i] U.S. Bureau of Labor Statistics, Women in the Labor Force: A Databook (Washington, DC: U.S. Department of Labor, 2013), Table 2.

[ii] U.S. Bureau of Labor Statistics, Women in the Labor Force: A Databook, Table 20.

[iii] Heather Boushey, “The New Breadwinners,” in The Shriver Report: A Woman’s Nation Changes Everything, ed. Heather Boushey and Ann O’Leary (Washington, DC: Center for American Progress, 2009); Sarah Jane Glynn, The New Breadwinners: 2010 Update (Washington, DC: Center for American Progress, 2012).

[iv] Sarah Jane Glynn, “The New Breadwinners: 2010 Update.”

[v] Eileen Appelbaum, Heather Boushey, and John Schmitt, Economic Importance of Women’s Rising Hours of Work: Time to Update Employment Standards (Washington, DC: Center for American Progress and the Center for Economic and Policy Research, 2014).

[vi] Ibid.

[vii] U.S. Bureau of Labor Statistics, Women in the Labor Force: A Databook, Table 2.

[viii] Carmen DeNavas-Walt, Bernadette D. Proctor, and Jessica C. Smith, Income, Poverty, and Health Insurance Coverage in the United States: 2012 (Washington, DC: U.S. Census Bureau, 2013), Table A-4.

[ix] The statistic refers to the 90^th to 10^th wage percentile ratio. Lawrence Mishel and others, State of Working America, 12th ed. (Washington, DC: Economic Policy Institute, 2013), Table 4-6, http://stateofworkingamerica.org/chart/swa-wages-table-4-6-hourly-wages-women-wage/.

[x] Jody Heymann, Alison Earle, and Jeffrey Hayes, The Work, Family, Equity Index: How Does the U.S. Measure Up? (Montreal, Canada: Institute for Health and Social Policy, McGill University, 2009), http://www.hreonline.com/pdfs/08012009Extra_McGillSurvey.pdf.

[xi] U.S. Bureau of Labor Statistics, “Table 32. Leave Benefits: Access, Private Industry Workers, National Compensation Survey, March 2013” (U.S. Department of Labor, 2013), http://www.bls.gov/ncs/ebs/benefits/2013/ownership/private/table21a.pdf.

[xii] U.S. Bureau of Labor Statistics, “Table 32. Leave Benefits: Access, Private Industry Workers, National Compensation Survey, March 2013.”

[xiii] Lynda Laughlin, Maternity Leave and Employment Patterns of First-Time Mothers: 1961–2008 (Washington, DC: U.S. Bureau of the Census, 2011), Table 11, http://www.census.gov/prod/2011pubs/p70-128.pdf.

[xiv] Francine D. Blau and Lawrence M. Kahn, Female Labor Supply: Why Is the US Falling Behind? (Bonn, Germany: Institute for the Study of Labor, 2013).

[xv] U.S. Bureau of Labor Statistics, “Table 32. Leave Benefits: Access, Private Industry Workers, National Compensation Survey, March 2013.”

[xvi] Susan J. Lambert and Julia R. Henly, “Nonstandard Work and Child-care Needs of Low-income Parents.” In Suzanne M. Bianchi, Lynne M. Casper, and Rosalind B. King, eds., Work, Family, Health, and Well-being (Lawrence Erlbaum Associates, Inc., 2005), pp. 473–92.

[xvii] Elaine Maag and Adam Carasso, “Taxation and the Family: What Is the Earned Income Tax Credit?” (Washington, DC: Tax Policy Center, 2014), http://www.taxpolicycenter.org/briefing-book/key-elements/family/eitc.cfm.

[xviii] Nada Eissa and Jeffrey B. Liebman, “Labor Supply Response to the Earned Income Tax Credit,” The Quarterly Journal of Economics 111, no. 2 (1996): 605–37; Chuck Marr, Chye-Ching Huang, and Arloc Sherman, Earned Income Tax Credit Promotes Work, Encourages Children’s Success at School, Research Finds (Washington, DC: Center on Budget and Policy Priorities, 2014), http://www.cbpp.org/files/6-26-12tax.pdf.

[xix] Center on Budget and Policy Priorities, The Earned Income Tax Credit (Washington, DC: Center on Budget and Policy Priorities, 2014), http://www.cbpp.org/files/policybasics-eitc.pdf.

[xx] Center on Budget and Policy Priorities, Policy Basics: The Child Tax Credit (Washington, DC: Center on Budget and Policy Priorities, 2014), http://www.cbpp.org/files/policybasics-ctc.pdf.

[xxi] Elaine Maag, “The Tax Policy Briefing Book: Taxation and the Family: How Does the Tax System Subsidize Child Care Expenses?” (Washington, DC: Tax Policy Center, 2013), http://www.taxpolicycenter.org/briefing-book/key-elements/family/child-care-subsidies.cfm.

[xxii] Maag, “The Tax Policy Briefing Book: Taxation and the Family: How Does the Tax System Subsidize Child Care Expenses?”

[xxiii] Gordon B. Dahl and Lance J. Lochner, “The Impact of Family Income on Child Achievement: Evidence from the Earned Income Tax Credit,” American Economic Review 102, no. 5 (August 2012): 1927–56.

[xxiv] 21st Century Worker Tax Cut Act, S. 2162, 113 Cong. 2 sess. (2014).

[xxv] U.S. Senator Patty Murray, “Senator Patty Murray Introduces The 21st Century Worker Tax Cut Act,” Press release, March 26, 2014, http://www.murray.senate.gov/public/index.cfm/2014/3/senator-patty-murray-introduces-the-21st-century-worker-tax-cut-act.

[xxvi] U.S. Senate Budget Committee, “The 21st Century Worker Tax Act,” (2014), http://www.budget.senate.gov/democratic/public/_cache/files/c548fb18-1c3e-4851-84c9-5680cbda388c/the-21st-century-worker-tax-cut-act.pdf.

[xxvii] U.S. Senator Patty Murray, “Senator Patty Murray Introduces The 21st Century Worker Tax Cut Act.”

[xxviii] Ibid.

[xxix] U.S. Senate Budget Committee, “The 21st Century Worker Tax Act.”

[xxx] David Madland and Keith Miller, “Raising the Minimum Wage Would Boost the Incomes of Millions of Women and Their Families” (Center for American Progress Action Fund, 2013), http://www.americanprogressaction.org/issues/labor/news/2013/12/09/80484/raising-the-minimum-wage-would-boost-the-incomes-of-millions-of-women-and-their-families/.

[xxxi] Melissa Boteach and Shawn Fremstad, “Putting Women at the Center of Policymaking,” in The Shriver Report: A Woman’s Nation Pushes Back from the Brink (Washington, DC: Center for American Progress, 2014), 244–79.

[xxxii] Ibid.

[xxxiii] Ibid.

[xxxiv] Ibid; NBC News, “Working Americans turn down pay raise to avoid ‘cliff effect’,” May 24, 2013, http://www.nbcnews.com/video/rock-center/51996100.

[xxxv] James J. Heckman and Dimitriy V. Masterov, “The Productivity Argument for Investing in Young Children,” Review of Agricultural Economics 29 (2007): 446–93.

[xxxvi] Arthur J. Reynolds et al., “Age 21 Cost-Benefit Analysis of the Title I Chicago Child-Parent Centers,” Educational Evaluation and Policy Analysis 24, no. 4 (Winter 2002): 267–303.

[xxxvii] Committee on Appropriations – Democrats, “Summary of Omnibus Appropriations Act,” United States House of Representatives, http://democrats.appropriations.house.gov/top-news/summary-of-omnibus-appropriations-act/ (last accessed May 2014); Harry Stein, “The Omnibus Spending Bill Reveals the Economic Consequences of the Murray-Ryan Budget Deal” (Center for American Progress, 2014), http://www.americanprogress.org/issues/budget/news/2014/01/17/82484/the-omnibus-spending-bill-reveals-the-economic-consequences-of-the-murray-ryan-budget-deal/.

[xxxviii] Stein, “The Omnibus Spending Bill Reveals the Economic Consequences of the Murray-Ryan Budget Deal.”

[xxxix] National Partnership for Women and Families, “Fact Sheet: The Family and Medical Insurance Leave Act (FAMILY Act)” (Washington, DC: National Partnership for Women & Families, 2014), http://www.nationalpartnership.org/research-library/work-family/paid-leave/family-act-fact-sheet.pdf.

[xl] National Partnership for Women and Families, “Paid Family & Medical Leave: An Overview,” (2012), http://go.nationalpartnership.org/site/DocServer/PFML_Overview_FINAL.pdf?docID=7847; Rhode Island Department of Labor and Training, “Temporary Disability Insurance,” http://www.dlt.ri.gov/tdi/ (last accessed May 2014).

[xli] Department of Labor, FY 2015 Department of Labor Budget in Brief (Washington, DC: Department of Labor, 2014), http://www.dol.gov/dol/budget/2015/PDF/FY2015BIB.pdf.

[xlii] Christopher Ruhm and Jackqueline L. Teague, “Parental Leave Policies in Europe and North America,” Gender and the Family Issues in the Workplace, 1997, 133–56.

[xliii] Ibid.

[xliv] MetLife Mature Market Institute, The MetLife Study of Caregiving Costs to Working Caregivers: Double Jeopardy for Baby Boomers Caring for Their Parents (Westport, CT: MetLife Mature Market Institute, 2011).

[xlv] Jane Waldfogel, “The Family Gap for Young Women in the United States and Britain: Can Maternity Leave Make a Difference?,” Journal of Labor Economics 16, no. 3 (1998): 505–45.

[xlvi] DeNavas-Walt, Proctor, and Smith, Income, Poverty, and Health Insurance Coverage in the United States: 2012, Table A-4.

[xlvii] National Women’s Law Center, “How the Wage Gap Hurts Women and Families,” (Washington, DC: National Women’s Law Center, 2013), http://www.nwlc.org/sites/default/files/pdfs/factorotherthan_sexfactsheet_5.30.12_final.pdf.

[xlviii] Heidi Hartmann and Jeffrey Hayes, How Equal Pay for Working Women Would Reduce Poverty and Grow the American Economy (Washington, DC: Institute for Women’s Policy Research, 2014).

[xlix] Ibid; U.S. Bureau of Economic Analysis, Widespread Economic Growth in 2012, News release, June 6, 2013), Table 4, http://bea.gov/newsreleases/regional/gdp_state/2013/pdf/gsp0613.pdf.

[l] Department of Labor, FY 2015 Department of Labor Budget in Brief.

[li] Madland and Miller, “Raising the Minimum Wage Would Boost the Incomes of Millions of Women and Their Families.”

[lii] David Cooper, Raising the Federal Minimum Wage to $10.10 Would Lift Wages for Million and Provide a Modest Economic Boost, (Washington, DC: Economic Policy Institute, 2013), http://www.epi.org/publication/raising-federal-minimum-wage-to-1010/.

[liii] Ibid.

[liv] Ibid.

[lv] Democratic Leader Nancy Pelosi, “When Women Succeed, America Succeeds: An Economic Agenda for Women and Families,” http://www.democraticleader.gov/Women_Succeed (last accessed May 2014).

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